Search Results

Search found 5104 results on 205 pages for 'evolutionary algorithm'.

Page 14/205 | < Previous Page | 10 11 12 13 14 15 16 17 18 19 20 21  | Next Page >

• Algorithm to get through a maze

  - by Sam

  Hello, We are currently programming a game (its a pretty unknown language: modula 2), And the problem we encountered is the following: we have a maze (not a perfect maze) in a 17 x 12 grid. The computer has to generate a way from the starting point (9, 12) to the end point (9, 1). I found some algorithms but they dont work when the robot has to go back: xxxxx x => x x xxx or: xxxxx x xxxxxx x x x x x xxxxxx x => x xxxxxxxxx I found a solution for the first example type but then the second type couldn't be solved and the solution I made up for the second type would cause the robot to get stuck in the first type of situation. It's a lot of code so i'll give the idea: WHILE (end destination not reached) DO { try to go right, if nothing blocks you: go right if you encounter a block, try up until you can go right, if you cant go up anymore try going down until you can go right, (starting from the place you first were blocked), if you cant go down anymore, try one step left and fill the spaces you tested with blocks. } This works for the first type of problem ... not for the second one. Now it could be that i started wrong so i am open for better algorithms or solutions specificaly to how i could improve my algorithm. Thanks a lot!!

  Read the article

• Accurate least-squares fit algorithm needed

  - by ggkmath

  I've experimented with the two ways of implementing a least-squares fit (LSF) algorithm shown here. The first code is simply the textbook approach, as described by Wolfram's page on LSF. The second code re-arranges the equation to minimize machine errors. Both codes produce similar results for my data. I compared these results with Matlab's p=polyfit(x,y,1) function, using correlation coefficients to measure the "goodness" of fit and compare each of the 3 routines. I observed that while all 3 methods produced good results, at least for my data, Matlab's routine had the best fit (the other 2 routines had similar results to each other). Matlab's p=polyfit(x,y,1) function uses a Vandermonde matrix, V (n x 2 matrix) and QR factorization to solve the least-squares problem. In Matlab code, it looks like: V = [x1,1; x2,1; x3,1; ... xn,1] % this line is pseudo-code [Q,R] = qr(V,0); p = R\(Q'*y); % performs same as p = V\y I'm not a mathematician, so I don't understand why it would be more accurate. Although the difference is slight, in my case I need to obtain the slope from the LSF and multiply it by a large number, so any improvement in accuracy shows up in my results. For reasons I can't get into, I cannot use Matlab's routine in my work. So, I'm wondering if anyone has a more accurate equation-based approach recommendation I could use that is an improvement over the above two approaches, in terms of rounding errors/machine accuracy/etc. Any comments appreciated! thanks in advance.

  Read the article

• Unexpected result in C algebra for search algorithm.

  - by Rhys

  Hi, I've implemented this search algorithm for an ordered array of integers. It works fine for the first data set I feed it (500 integers), but fails on longer searches. However, all of the sets work perfectly with the other four search algorithms I've implemented for the assignment. This is the function that returns a seg fault on line 178 (due to an unexpected negative m value). Any help would be greatly appreciated. CODE: 155 /* perform Algortihm 'InterPolationSearch' on the set 156 * and if 'key' is found in the set return it's index 157 * otherwise return -1 */ 158 int 159 interpolation_search(int *set, int len, int key) 160 { 161 int l = 0; 162 int r = len - 1; 163 int m; 164 165 while (set[l] < key && set[r] >= key) 166 { 167 168 printf ("m = l + ((key - set[l]) * (r - l)) / (set[r] - set[l])\n"); 169 170 printf ("m = %d + ((%d - %d) * (%d - %d)) / (%d - %d);\n", l, key, set[l], r, l, set[r], set[l]); 171 m = l + ((key - set[l]) * (r - l)) / (set[r] - set[l]); 172 printf ("m = %d\n", m); 173 174 #ifdef COUNT_COMPARES 175 g_compares++; 176 #endif 177 178 if (set[m] < key) 179 l = m + 1; 180 else if (set[m] > key) 181 r = m - 1; 182 else 183 return m; 184 } 185 186 if (set[l] == key) 187 return l; 188 else 189 return -1; 190 } OUTPUT: m = l + ((key - set[l]) * (r - l)) / (set[r] - set[l]) m = 0 + ((68816 - 0) * (100000 - 0)) / (114836 - 0); m = -14876 Thankyou! Rhys

  Read the article

• Resizing image algorithm in python

  - by hippocampus

  So, I'm learning my self python by this tutorial and I'm stuck with exercise number 13 which says: Write a function to uniformly shrink or enlarge an image. Your function should take an image along with a scaling factor. To shrink the image the scale factor should be between 0 and 1 to enlarge the image the scaling factor should be greater than 1. This is not meant as a question about PIL, but to ask which algorithm to use so I can code it myself. I've found some similar questions like this, but I dunno how to translate this into python. Any help would be appreciated. I've come to this: import image win = image.ImageWin() img = image.Image("cy.png") factor = 2 W = img.getWidth() H = img.getHeight() newW = int(W*factor) newH = int(H*factor) newImage = image.EmptyImage(newW, newH) for col in range(newW): for row in range(newH): p = img.getPixel(col,row) newImage.setPixel(col*factor,row*factor,p) newImage.draw(win) win.exitonclick() I should do this in a function, but this doesn't matter right now. Arguments for function would be (image, factor). You can try it on OP tutorial in ActiveCode. It makes a stretched image with empty columns :.

  Read the article

• Using Traveling Salesman Solver to Decide Hamiltonian Path

  - by Firas Assaad

  This is for a project where I'm asked to implement a heuristic for the traveling salesman optimization problem and also the Hamiltonian path or cycle decision problem. I don't need help with the implementation itself, but have a question on the direction I'm going in. I already have a TSP heuristic based on a genetic algorithm: it assumes a complete graph, starts with a set of random solutions as a population, and works to improve the population for a number of generations. Can I also use it to solve the Hamiltonian path or cycle problems? Instead of optimizing to get the shortest path, I just want to check if there is a path. Now any complete graph will have a Hamiltonian path in it, so the TSP heuristic would have to be extended to any graph. This could be done by setting the edges to some infinity value if there is no path between two cities, and returning the first path that is a valid Hamiltonian path. Is that the right way to approach it? Or should I use a different heuristic for Hamiltonian path? My main concern is whether it's a viable approach since I can be somewhat sure that TSP optimization works (because you start with solutions and improve them) but not if a Hamiltonian path decider would find any path in a fixed number of generations. I assume the best approach would be to test it myself, but I'm constrained by time and thought I'd ask before going down this route... (I could find a different heuristic for Hamiltonian path instead)

  Read the article

• Video-codec rater by image comparison algorithm?

  - by Andreas Hornig

  Hi, perhaps anyone knows if this is possible. comparing image quality is almost imposible to describe without subjective influences. When someone rates an image quality as good there is at least one person, that doesn't think so. human preferences are always different. So, I would like to know if there is away to "rate" the image quality by an algorithm that compares the original image to the produced one in following issues colour change(difference pixel by pixel blur rate artifacts and macroblocking the first one would be the easiest one because you could check just the diffeence in colours and can give 3 values in +- of each hex-value both last once I don't know if this is possible, but the blocking could be detected by edge-finding. and the king's quest would be to do that for more then just one image, because video is done with several frames. perhaps you expert programmers could tell me, if such an automated algo can be done to bring some objective measurement divice into rating image quality. this could perhaps calm down some h.264 is better than x264 and better than vp8 and blaaah people :) Andreas 1st posted here http://www.hdtvtotal.com/index.php?name=PNphpBB2&file=viewtopic&p=9705

  Read the article

• Bitap algorithm in Java [closed]

  - by davit-datuashvili

  The following is the bitap algorithm according to Wikipedia. Can someone translate this to Java? #include <string.h> #include <limits.h> const char *bitap_bitwise_search(const char *text, const char *pattern) { int m = strlen(pattern); unsigned long R; unsigned long pattern_mask[CHAR_MAX+1]; int i; if (pattern[0] == '\0') return text; if (m > 31) return "The pattern is too long!"; /* Initialize the bit array R */ R = ~1; /* Initialize the pattern bitmasks */ for (i=0; i <= CHAR_MAX; ++i) pattern_mask[i] = ~0; for (i=0; i < m; ++i) pattern_mask[pattern[i]] &= ~(1UL << i); for (i=0; text[i] != '\0'; ++i) { /* Update the bit array */ R |= pattern_mask[text[i]]; R <<= 1; if (0 == (R & (1UL << m))) return (text + i - m) + 1; } return NULL; }

  Read the article

• Average performance of binary search algorithm?

  - by Passionate Learner

  http://en.wikipedia.org/wiki/Binary_search_algorithm#Average_performance BinarySearch(int A[], int value, int low, int high) { int mid; if (high < low) return -1; mid = (low + high) / 2; if (A[mid] > value) return BinarySearch(A, value, low, mid-1); else if (A[mid] < value) return BinarySearch(A, value, mid+1, high); else return mid; } If the integer I'm trying to find is always in the array, can anyone help me write a program that can calculate the average performance of binary search algorithm? I know I can do this by actually running the program and counting the number of calls, but what I'm trying to do here is to do it without calling the function. I'm not asking for a time complexity, I'm trying to calculate the average number of calls. For example, the average number of calls to find a integer in A[2], it would be 1.67 (5/3).

  Read the article

• Open space sitting optimization algorithm

  - by Georgy Bolyuba

  As a result of changes in the company, we have to rearrange our sitting plan: one room with 10 desks in it. Some desks are more popular than others for number of reasons. One solution would be to draw a desk number from a hat. We think there is a better way to do it. We have 10 desks and 10 people. Lets give every person in this contest 50 hypothetical tokens to bid on the desks. There is no limit of how much you bid on one desk, you can put all 50, which would be saying "I want to sit only here, period". You can also say "I do not care" by giving every desk 5 tokens. Important note: nobody knows what other people are doing. Everyone has to decide based only on his/her best interest (sounds familiar?) Now lets say we obtained these hypothetical results: # | Desk# >| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 1 | Alise | 30 | 2 | 2 | 1 | 0 | 0 | 0 | 15 | 0 | 0 | = 50 2 | Bob | 20 | 15 | 0 | 10 | 1 | 1 | 1 | 1 | 1 | 0 | = 50 ... 10 | Zed | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | = 50 Now, what we need to find is that one (or more) configuration(s) that gives us maximum satisfaction (i.e. people get desks they wanted taking into account all the bids and maximizing on the total of the group. Naturally the assumption is the more one bade on the desk the more he/she wants it). Since there are only 10 people, I think we can brute force it looking into all possible configurations, but I was wondering it there is a better algorithm for solving this kind of problems?

  Read the article

• Number Algorithm

  - by James

  I've been struggling to wrap my head around this for some reason. I have 15 bits that represent a number. The bits must match a pattern. The pattern is defined in the way the bits start out: they are in the most flush-right representation of that pattern. So say the pattern is 1 4 1. The bits will be: 000000010111101 So the general rule is, take each number in the pattern, create that many bits (1, 4 or 1 in this case) and then have at least one space separating them. So if it's 1 2 6 1 (it will be random): 001011011111101 Starting with the flush-right version, I want to generate every single possible number that meets that pattern. The # of bits will be stored in a variable. So for a simple case, assume it's 5 bits and the initial bit pattern is: 00101. I want to generate: 00101 01001 01010 10001 10010 10100 I'm trying to do this in Objective-C, but anything resembling C would be fine. I just can't seem to come up with a good recursive algorithm for this. It makes sense in the above example, but when I start getting into 12431 and having to keep track of everything it breaks down.

  Read the article

• priority queue with limited space: looking for a good algorithm

  - by SigTerm

  This is not a homework. I'm using a small "priority queue" (implemented as array at the moment) for storing last N items with smallest value. This is a bit slow - O(N) item insertion time. Current implementation keeps track of largest item in array and discards any items that wouldn't fit into array, but I still would like to reduce number of operations further. looking for a priority queue algorithm that matches following requirements: queue can be implemented as array, which has fixed size and _cannot_ grow. Dynamic memory allocation during any queue operation is strictly forbidden. Anything that doesn't fit into array is discarded, but queue keeps all smallest elements ever encountered. O(log(N)) insertion time (i.e. adding element into queue should take up to O(log(N))). (optional) O(1) access for *largest* item in queue (queue stores *smallest* items, so the largest item will be discarded first and I'll need them to reduce number of operations) Easy to implement/understand. Ideally - something similar to binary search - once you understand it, you remember it forever. Elements need not to be sorted in any way. I just need to keep N smallest value ever encountered. When I'll need them, I'll access all of them at once. So technically it doesn't have to be a queue, I just need N last smallest values to be stored. I initially thought about using binary heaps (they can be easily implemented via arrays), but apparently they don't behave well when array can't grow anymore. Linked lists and arrays will require extra time for moving things around. stl priority queue grows and uses dynamic allocation (I may be wrong about it, though). So, any other ideas?

  Read the article

• Algorithm to determine which points should be visible on a map based on zoom

  - by lgratian

  Hi! I'm making a Google Maps-like application for a course at my Uni (not something complex, it should load the map of a city for example, not the whole world). The map can have many layers, including markers (restaurants, hospitals, etc.) The problem is that when you have many points and you zoom out the map it doesn't look right. At this zoom level only some points need to be visible (and at the maximum map size, all points). The question is: how can you determine which points should be visible for a specified zoom level? Because I have implemented a PR Quadtree to speed up rendering I thought that I could define some "high-priority" markers (that are always visible, defined in the map editor) and put them in a queue. At each step a marker is removed from the queue and all it's neighbors that are at least D units away (D depends on the zoom levels) are chosen and inserted in the queue, and so on. Is there any better way than the algorithm I thought of? Thanks in advance!

  Read the article

• Algorithm to see if keywords exist inside a string

  - by rksprst

  Let's say I have a set of keywords in an array {"olympics", "sports tennis best", "tennis", "tennis rules"} I then have a large list (up to 50 at a time) of strings (or actually tweets), so they are a max of 140 characters. I want to look at each string and see what keywords are present there. In the case where a keyword is composed of multiple words like "sports tennis best", the words don't have to be together in the string, but all of them have to show up. I've having trouble figuring out an algorithm that does this efficiently. Do you guys have suggestions on a way to do this? Thanks! Edit: To explain a bit better each keyword has an id associated with it, so {1:"olympics", 2:"sports tennis best", 3:"tennis", 4:"tennis rules"} I want to go through the list of strings/tweets and see which group of keywords match. The output should be, this tweet belongs with keyword #4. (multiple matches may be made, so anything that matches keyword 2, would also match 3 -since they both contain tennis). When there are multiple words in the keyword, e.g. "sports tennis best" they don't have to appear together but have to all appear. e.g. this will correctly match: "i just played tennis, i love sports, its the best"... since this string contains "sports tennis best" it will match and be associated with the keywordID (which is 2 for this example).

  Read the article

• Algorithm for finding the best routes for food distribution in game

  - by Tautrimas

  Hello, I'm designing a city building game and got into a problem. Imagine Sierra's Caesar III game mechanics: you have many city districts with one market each. There are several granaries over the distance connected with a directed weighted graph. The difference: people (here cars) are units that form traffic jams (here goes the graph weights). Note: in Ceasar game series, people harvested food and stockpiled it in several big granaries, whereas many markets (small shops) took food from the granaries and delivered it to the citizens. The task: tell each district where they should be getting their food from while taking least time and minimizing congestions on the city's roads. Map example Sample diagram Suppose that yellow districts need 7, 7 and 4 apples accordingly. Bluish granaries have 7 and 11 apples accordingly. Suppose edges weights to be proportional to their length. Then, the solution should be something like the gray numbers indicated on the edges. Eg, first district gets 4 apples from the 1st and 3 apples from the 2nd granary, while the last district gets 4 apples from only the 2nd granary. Here, vertical roads are first occupied to the max, and then the remaining workers are sent to the diagonal paths. Question What practical and very fast algorithm should I use? I was looking at some papers (Congestion Games: Optimization in Competition etc.) describing congestion games, but could not get the big picture. Any help is very appreciated! P. S. I can post very little links and no images because of new user restriction.

  Read the article

• Is my heuristic algorithm correct? (Sudoku solver)

  - by Aposperite

  First of -yes this IS a homework- but it's primarily a theoretical question rather than a practical one, I am simply asking a confirmation if I am thinking correctly or any hints if I am not. I have been asked to compile a simple Sudoku solver (on Prolog but that is not so important right now) with the only limitation being that it must utilize a heuristic function using Best-First Algorithm. The only heuristic function I have been able to come up with is explained below: 1. Select an empty cell. 1a. If there are no empty cells and there is a solution return solution. Else return No. 2. Find all possible values it can hold. %% It can't take values currently assigned to cells on the same line/column/box. 3. Set to all those values a heuristic number starting from 1. 4. Pick the value whose heuristic number is the lowest && you haven't checked yet. 4a. If there are no more values return no. 5. If a solution is not found: GoTo 1. Else Return Solution. // I am sorry for errors in this "pseudo code." If you want any clarification let me know. So am I doing this right or is there any other way around and mine is false? Thanks in advance.

  Read the article

• Discover periodic patterns in a large data-set

  - by Miner

  I have a large sequence of tuples on disk in the form (t1, k1) (t2, k2) ... (tn, kn) ti is a monotonically increasing timestamp and ki is a key (assume a fixed length string if needed). Neither ti nor ki are guaranteed to be unique. However, the number of unique tis and kis is huge (millions). n itself is very large (100 Million+) and the size of k (approx 500 bytes) makes it impossible to store everything in memory. I would like to find out periodic occurrences of keys in this sequence. For example, if I have the sequence (1, a) (2, b) (3, c) (4, b) (5, a) (6, b) (7, d) (8, b) (9, a) (10, b) The algorithm should emit (a, 4) and (b, 2). That is a occurs with a period of 4 and b occurs with a period of 2. If I build a hash of all keys and store the average of the difference between consecutive timestamps of each key and a std deviation of the same, I might be able to make a pass, and report only the ones that have an acceptable std deviation(ideally, 0). However, it requires one bucket per unique key, whereas in practice, I might have very few really periodic patterns. Any better ways?

  Read the article

• Quickest algorithm for finding sets with high intersection

  - by conradlee

  I have a large number of user IDs (integers), potentially millions. These users all belong to various groups (sets of integers), such that there are on the order of 10 million groups. To simplify my example and get to the essence of it, let's assume that all groups contain 20 user IDs (i.e., all integer sets have a cardinality of 100). I want to find all pairs of integer sets that have an intersection of 15 or greater. Should I compare every pair of sets? (If I keep a data structure that maps userIDs to set membership, this would not be necessary.) What is the quickest way to do this? That is, what should my underlying data structure be for representing the integer sets? Sorted sets, unsorted---can hashing somehow help? And what algorithm should I use to compute set intersection)? I prefer answers that relate C/C++ (especially STL), but also any more general, algorithmic insights are welcome. Update Also, note that I will be running this in parallel in a shared memory environment, so ideas that cleanly extend to a parallel solution are preferred.

  Read the article

• Need some help understanding this problem about maximizing graph connectivity

  - by Legend

  I was wondering if someone could help me understand this problem. I prepared a small diagram because it is much easier to explain it visually. Problem I am trying to solve: 1. Constructing the dependency graph Given the connectivity of the graph and a metric that determines how well a node depends on the other, order the dependencies. For instance, I could put in a few rules saying that node 3 depends on node 4 node 2 depends on node 3 node 3 depends on node 5 But because the final rule is not "valuable" (again based on the same metric), I will not add the rule to my system. 2. Execute the request order Once I built a dependency graph, execute the list in an order that maximizes the final connectivity. I am not sure if this is a really a problem but I somehow have a feeling that there might exist more than one order in which case, it is required to choose the best order. First and foremost, I am wondering if I constructed the problem correctly and if I should be aware of any corner cases. Secondly, is there a closely related algorithm that I can look at? Currently, I am thinking of something like Feedback Arc Set or the Secretary Problem but I am a little confused at the moment. Any suggestions? PS: I am a little confused about the problem myself so please don't flame on me for that. If any clarifications are needed, I will try to update the question.

  Read the article

• Fast Lightweight Image Comparisson Metric Algorithm

  - by gav

  Hi All, I am developing an application for the Android platform which contains 1000+ image filters that have been 'evolved'. When a user selects a photo I want to present the most relevant filters first. This 'relevance' should be dependent on previous use cases. I have already developed tools that register when a filtered image is saved; this combination of filter and image can be seen as the training data for my system. The issue is that the comparison must occur between selecting an image and the next screen coming up. From a UI point of view I need the whole process to take less that 4 seconds; select an image- obtain a metric to use for similarity - check against use cases - return 6 closest matches. I figure with 4 seconds I can use animations and progress dialogs to keep the user happy. Due to platform contraints I am fairly limited in the computational expense of the algorithm. I have implemented a technique adapted from various online tutorials for running C code on the G1 and hence this language is available Specific Constraints; Qualcomm® MSM7201A™, 528 MHz Processor 320 x 480 Pixel bitmap in 32 bit ARGB ~ 2 seconds computational time for the native method to get the metric ~ 2 seconds to compare the metric of the current image with training data This is an academic project so all ideas are welcome, anything you can think of or have heard about would be of interest to me. My ideas; I want to keep the complexity down (O(n*m)?) by using pixel data only rather than a neighbourhood function I was looking at using the Colour historgram/Greyscale histogram/Texture/Entropy of the image, combining them to make the measure. There will be an obvious loss of information but I need the resultant metric to be substantially smaller than the memory footprint of the image (~0.512 MB) As I said, any ideas to direct my research would be fantastic. Kind regards, Gavin

  Read the article

• Warshall Algorithm Logic - Stuck

  - by stan

  I am trying to use this logic to understand what is going on with the adjacency matrix, but i am massivley confused where it says about interspacing for a b c d ..... Could anyone explain what is going on here? Thank you (tagged as java as its the language this was demonstarted to us in, so if anyone posted any code examples they could see it was in that language) http://compprog.wordpress.com/2007/11/15/all-sources-shortest-path-the-floyd-warshall-algorithm/ Here is the code: for (k = 0; k < n; ++k) { for (i = 0; i < n; ++i) for (j = 0; j < n; ++j) /* If i and j are different nodes and if the paths between i and k and between k and j exist, do */ if ((dist[i][k] * dist[k][j] != 0) && (i != j)) /* See if you can't get a shorter path between i and j by interspacing k somewhere along the current path */ if ((dist[i][k] + dist[k][j] < dist[i][j]) || (dist[i][j] == 0)) dist[i][j] = dist[i][k] + dist[k][j];

  Read the article

• Algorithm for count-down timer that can add on time

  - by Person

  I'm making a general timer that has functionality to count up from 0 or count down from a certain number. I also want it to allow the user to add and subtract time. Everything is simple to implement except for the case in which the timer is counting down from some number, and the user adds or subtracts time from it. For example: (m_clock is an instance of SFML's Clock) float Timer::GetElapsedTime() { if ( m_forward ) { m_elapsedTime += m_clock.GetElapsedTime() - m_elapsedTime; } else { m_elapsedTime -= m_elapsedTime - m_startingTime + m_clock.GetElapsedTime(); } return m_elapsedTime; } To be a bit more clear, imagine that the timer starts at 100 counting down. After 10 seconds, the above function would look like 100 -= 100 - 100 + 10 which equals 90. If it was called after 20 more seconds it would look like 90 -= 90 - 100 + 30 which equals 70. This works for normal counting, but if the user calls AddTime() ( just m_elapsedTime += arg ) then the algorithm for backwards counting fails miserably. I know that I can do this using more members and keeping track of previous times, etc. but I'm wondering whether I'm missing some implementation that is extremely obvious. I'd prefer to keep it as simple as possible in that single operation.

  Read the article

• problem with binarysearch algorithm

  - by arash

  hi friends,the code below belongs to binary search algorithm,user enter numbers in textbox1 and enter the number that he want to fing with binarysearch in textbox2.i have a problem with it,that is when i enter for example 15,21 in textbox1 and enter 15 in textbox2 and put brakpoint on the line i commented below,and i understood that it doesnt put the number in textbox2 in searchnums(commented),for more explanation i comment in code.thanks in advance public void button1_Click(object sender, EventArgs e) { int searchnums = Convert.ToInt32(textBox2.Text);//the problem is here,the value in textbox2 doesnt exist in searchnums and it has value 0. int result = binarysearch(searchnums); MessageBox.Show(result.ToString()); } public int binarysearch(int searchnum) { string[] source = textBox1.Text.Split(','); int[] nums = new int[source.Length]; for (int i = 0; i < source.Length; i++) { nums[i] = Convert.ToInt32(source[i]); } int first =0; int last = nums.Length; int mid = (int)Math.Floor(nums.Length / 2.0); while (1<= nums.Length) { if (searchnum < nums[mid]) { last = mid - 1; } if (searchnum > nums[mid]) { first = mid + 1; } else { return nums[mid]; } } return -1; }

  Read the article

• GSM Cell Towers Location & Triangulation Algorithm (Similar to OpenCellID / Skyhook / Google's MyLocation)

  - by ranabra

  Hi all, assuming I have a Fingerprint DB of Cell towers. The data (including Long. & Lat. CellID, signal strength, etc) is achieved by 'wardriving', similar to OpenCellID.org. I would like to be able to get the location of the client mobile phone without GPS (similar to OpenCellID / Skyhook Wireless/ Google's 'MyLocation'), which sends me info on the Cell towers it "sees" at the moment: the Cell tower connected to, and another 6 neighboring cell towers (assuming GSM). I have read and Googled it for a long time and came across several effective theories, such as using SQL 2008 Spatial capabilities, or using an euclidean algorithm, or Markov Model. However, I am lacking a practical solution, preferably in C# or using SQL 2008 :) The location calculation will be done on the server and not on the client mobile phone. the phone's single job is to send via HTTP/GPRS, the tower it's connected to and other neighboring cell towers. Any input is appreciated, I have read so much and so far haven't really advanced much. Thanx

  Read the article

• Need some help understanding this problem

  - by Legend

  I was wondering if someone could help me understand this problem. I prepared a small diagram because it is much easier to explain it visually. Problem I am trying to solve: 1. Constructing the dependency graph Given the connectivity of the graph and a metric that determines how well a node depends on the other, order the dependencies. For instance, I could put in a few rules saying that node 3 depends on node 4 node 2 depends on node 3 node 3 depends on node 5 But because the final rule is not "valuable" (again based on the same metric), I will not add the rule to my system. 2. Execute the request order Once I built a dependency graph, execute the list in an order that maximizes the final connectivity. First and foremost, I am wondering if I constructed the problem correctly and if I should be aware of any corner cases. Secondly, is there a closely related algorithm that I can look at? Currently, I am thinking of something like Feedback Arc Set or the Secretary Problem but I am a little confused at the moment. Any suggestions? PS: I am a little confused about the problem myself so please don't flame on me for that. If any clarifications are needed, I will try to update the question.

  Read the article

• Reducing a set of non-unique elements via transformations

  - by Andrey Fedorov

  I have: 1) a "starting set" of not-necessarily-unique elements, e.x. { x, y, z, z }, 2) a set of transformations, e.x. (x,z) = y, (z,z) = z, x = z, y = x, and 3) a "target set" that I am trying to get by applying transformations to the starting set, e.x. { z }. I'd like to find an algorithm to generate the (possibly infinite) possible applications of the transformations to the starting set that result in the target set. For example: { x, y, z, z }, y => x { x, x, z, z }, x => z { z, x, z, z }, x => z { z, z, z, z }, (z, z) => z { z, z, z }, (z, z) => z { z, z }, (z, z) => z { z } This sounds like something that's probably an existing (named) problem, but I don't recognize it. Can anyone help me track it down, or suggest further reading on something similar?

  Read the article

< Previous Page | 10 11 12 13 14 15 16 17 18 19 20 21  | Next Page >